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Scarce resources, strict take-back legislations, decreasing life cycle of products and increasing competition are compelled original equipment manufacturers (OEMs) to collect and reuse their returned products. Remanufacturing is a well-known and widely used environment-friendly manufacturing to evaluate product returns. Moreover, with remanufacturing, OEMs offer environment-friendly products to environmentally concerned consumers, also known as green consumer. This study aims to develop a prediction model to determine consumer purchase behavior of remanufactured products. We investigate the data with a survey of closed-end questions conducted among 400 residents of Ankara, Turkey. We consider several factors that influence consumers preferences in purchasing process of remanufactured products. The suggested model predicts consumer behavior of remanufactured products with logistic regression analysis. The results show that some factors have effects on consumer purchase behavior of remanufactured product such as low prices, company reliability and product promotion changes consumer behavior from no purchasing to purchasing remanufactured products.

PurposeTo investigate the relationship between the choice of integrated or functional logistics providers by Brazilian shippers and: the type of their manufacturing process structure, and the level of sophistication of their logistics function, as well as the impact on that choice of possible interactions between these two characteristics of the shippers.Design/methodology/approachData were collected in a comprehensive survey on the use of 3PL service providers in Brazil using a sample of 93 large Brazilian shippers; The analysis tests three research questions on the individual and combined relationships of logistics sophistication, measured on a logistics sophistication index (LSI), and process type (according to Goldratt's V‐A‐T classification for materials flow analysis) with the choice of type of 3PL provider; the methods of analysis were cluster and logistics regression analysis.FindingsThe paper finds: support for an association of sophisticated logistics functions and a preference for integrated 3PLs; support for an association between the A‐type production process structure and preference for integrated 3PLs; and of V and T types for functional 3PLs. However, it also finds that shippers with type T process structure and more sophisticated logistics tend to favor integrated 3PLs.Research limitations/implicationsOne limitation is that logistics performance is not considered; future studies may further refine the proposed framework for segmentation.Practical implicationsThe paper advocates the use of models by providers to segment their customers, and better understanding by shippers of prevailing trends in logistics outsourcing according to their process structure and characteristics of their logistics function.Originality/valueThe paper unveils significant relationships between shipper sophistication of logistics function, manufacturing process structures, and the choice of type of 3PL. It also proposes a new framework for segmenting the 3PL service provider market in terms of sophistication of the logistics function and the logistics task implied by the type of operation.

Road accidents have become more common these days and it is pathetic when the accidents happen due to ignorance. The research objective is focused on university students, creating awareness about road safety and improving a sustainable traffic management scenario in the Kingdom of Saudi Arabia. An analytical hierarchy process and a logistic regression model were used to determine the risk priorities ranking of severity factors based on the comparisons of different driver behaviour factors. A cross-sectional survey was conducted among 3200 university students in Saudi Arabia to evaluate the risk associated with accident factors. The main factors taken for risk analysis were Stability during driving, not adhering to rules, committing human errors, Insufficient Visibility, Facing Vehicles Issues. The model estimation analysis revealed the severity, which was based on the student's behavioural factors as a driver which contributed to the high fatality. It is further proposed to teach an interdisciplinary course on Traffic Management to various university students. The awareness towards traffic sense and safety rules would bring down the accidents rates and help the government to maintain smooth traffic density.

Logistic Regression modelling techniques are applied to the problem of describing Marine Corps officer monthly attrition based upon such factors as grade, military occupation specialty, promotion zone, season and gender. The monthly unemployment rate is considered as a useful covariate. The monthly losses are rather rare events and the ability to support the suggested models is not firm. Some exploratory computations are performed in order to examine the effect of using these models in conjunction with previously established annual rate generating models. ; HQ USMC, Code MI Washington, DC 20380-0001 ; NPS DFR and Headquarters, United States Marine Corps, Code MI,Washington, DC. ; NPS DFR and Headquarters, United States Marine Corps, Code MI ; ORWHl ; Approved for public release; distribution is unlimited.

Malaria epidemics are widespread in the tropics. Studies showed that malaria mitigation depends on case management, vector control and use of preventive measures. However, knowledge, attitude and practice (KAP) regarding malaria are paramount in the mitigation campaign which has not been given relevance in Sub-Sahara Africa. This study explores factors influencing KAP regarding malaria in Gwagwalada. A cross-sectional survey was done in four different sites in Gwagwalada between March and September 2016. A structured validated questionnaire was used to obtain information from 384 respondents. There was a statistical comparison of the KAP among the different sites. Majority of participants had heard about malaria (99.3%) but only 20% had good knowledge and 14.4% have good practice scores. There was no significant difference in the KAP scores of the four different sites examined. Of the selected socio-demographic predictors, occupation and education of participants were significantly different for attitude scores, while age and occupation were associated with knowledge scores. Only marital status was significant with good practice. The study found increased odds of good knowledge if the participants worked with the government (OR:1.34; .95CI:0.50,3.48) and decreased in odds of having good knowledge if the participants were older than 47 years (OR:0.98; 0.95CI:0.34,3.17). At multivariate level, only respondent's education significantly predicts attitude level (P<0.05) while age and occupation were independent predictors of level of knowledge. Age and education are key determinant factors of malaria KAP in the study area. Therefore, health education should target people with lower education and older age at community level.

AbstractAdequate prediction of a response variable using a multiple linear regression model is shown in this article to be related to the presence of multicollinearities among the predictor variables. If strong multicollinearities are present in the data, this information can be used to determine when prediction is likely to be accurate. A region of prediction, R, is proposed as a guide for prediction purposes. This region is related to a prediction interval when the matrix of predictor variables is of full column rank, but it can also be used when the sample is undersized. The Gorman‐Toman ten‐variable data is used to illustrate the effectiveness of the region R.

AbstractMulticollinearity and nonnormal errors are problems often encountered in the application of linear regression. Estimators are proposed for dealing with the simultaneous occurrence of both multicollinearity and nonnormality. These estimators are developed by combining biased estimation techniques with certain robust criteria. An iteratively reweighted least‐squares procedure is used to compute the estimates. The performance of the combined estimators is studied empirically through Monte Carlo experiments structured according to factorial designs. With respect to a mean‐squared‐error criterion, the combined estimators are superior to ordinary least‐squares, pure biased estimators, and pure robust estimators when multicollinearity and nonnormality are present. The loss in efficiency for the combined estimators relative to least squares is small when these problems do not occur. Some guidelines for the use of these combined estimators are given.

This study investigated the socio-economic determinants at the individual and contextual level of household poverty in Indonesia. The data used in this study is drawn from the March 2020 Indonesia-National Socio-Economic Survey (Susenas) provided by BPS, Statistics-Indonesia. The data were analyzed using the Multilevel Logistics Regression Model. This study indicates that the achievement of the Human Development Index at the provincial level affects the reduction of the poor at the household level. Moreover, at the individual level, household size, education level, and employment status of the household head significantly affect household poverty. The results of this study underscore the need to look beyond the influence of individual-level factors in addressing regional variations in household poverty in Indonesia. Therefore, Government policies to increase human development in provinces with low HDI are needed.